Reconstruction of local patient doses in computed tomography

ABSTRACT

In order to reduce an x-ray dose applied to a patient, it is necessary to know the dose absorbed by the patient. According to the present invention, there is provided a method of determining a local patient dose applied to a patient where after the reconstruction of the scan data into a diagnostic image, the scan data are backprojected into the patient volume, using the attenuation information of the diagnostic image to form a spatially varying photon fluence map. In parallel, the diagnostic image is segmented into anatomical structures to which dose-weighting factors are assigned. The locally absorbed dose is then calculated on the basis of the fluence map and the corresponding dose weights.

The present invention relates generally to methods and apparatus for“computed tomography” (CT) and other radiation imaging systems and moreparticularly to a method of determining a local patient dose applied toa patient in computed tomography, an imaging processing device and acomputer program for an image processing device.

In at least some CT imaging system configurations, an x-ray sourceprojects a fan-shaped beam such that it is collimated to lie within anX-Y plane of a Cartesian coordinate system, which is usually referred toas the “imaging plane”. The x-ray beam passes through an object beingimaged, such as a medical patient. The beam, after being attenuated bythe object, impinges upon an array of radiation detectors. The intensityof the attenuated beam radiation received at a detector array isdependent upon the attenuation of the x-ray beam by the object beingimaged. Each detector element of the detector array generates anelectrical signal indicating the beam attenuation at the detectorlocation. The attenuation measurements from all the detectors areacquired separately to produce a transmission profile and represent scandata.

In known third generation CT systems, the x-ray source and the detectorarray are rotated with a gantry within the imaging plane and around theobject to be imaged, such that an angle at which the x-ray beamintersects the object changes constantly. The used x-ray sources usuallyinclude x-ray tubes, which emit the x-ray beam at a focal spot. X-raydetectors may include a collimator for collimating x-ray beams receivedat the detector, a scintillator adjacent to the collimator andphotodetectors adjacent to the scintillator. A group of x-rayattenuation measurements, i.e. projection data from the detector arrayat one ganrty angle is referred to as a “view”. A “scan” of the objectfor generating the necessary scan data comprises a set of views made atdifferent gantry angles, or view angles, during one revolution of thex-ray source and detector.

In an axial scan, the projection data is processed to construct an imagethat corresponds to a two-dimensional slice taken through the object. Aknown method for reconstructing an image from a set of projection dataor scan data is the filtered back projection technique. This processconverts the attenuation measurements from a scan into integers called“CT numbers” or “Hounsfield units”, which are used to control greyvalues of a corresponding diagnostic image.

In other words, in the known CT scanners, the recorded projectionsacquired during an object or patient scan (scan data) are mathematicallyreconstructed into a tomographic image with grey levels indicatingHounsfield units. The tomographic image is used by, for example, aclinician for diagnostic purposes and is referred to as the diagnosticimage in the following.

Currently, attempts are made to reduce doses applied to patients duringCT scans. However, an identification of an exceeding dose and anoptimation of the dose applied to the patient during the scan requiresthe exact knowledge of the doses actually applied to the patient duringthe scan.

The program “WinDose” (Kalendar, W. A., Schmidt B., Zankl M., Schmidt M.(1999), A PC program for estimating organdose and effective dose valuesin computed tomography. European Radiology 9: 555-562) is a PC programfor estimating organdose and effective dose values in computedtomography and calculates the patient dose applied to the patient, onthe basis of only a few parameters of the patient. Primarily, theseparameters are referring to the circumference and weight of the patientand the settings of the x-ray tube, such as the applied power (mA, kVp).Then, on the basis of tables, and by using a Monte Carlo simulation,which has been computed with respect to a standard patient having astandard shape, an integral dose of the most important organs may bedetermined. However, this computer program does not deliver sufficientresults in case the patient differs from the standard data, for examplein pediatrics.

WO 00/07667 relates to a radiotherapy verification system, wherein adose delivered to the patient may be computed on the basis of a model ofthe patient to estimate values of energy fluence prior to absorption bythe patient and overlapping of the various radiation beams passingthrough the patient. A model may be constructed from a known geometry ofthe radiation therapy machine and estimated properties of the patient orstandard patient as deduced from a pre-treatment tomography.Accordingly, in order to compute a dose delivered to the person in thesystem known from WO 00/07667, either a standard patient has to be usedfor the computation of the dose resulting in the same insufficientresults as the program “WinDose” or a pre-treatment tomogram has to becarried out which increases the overall dose applied to the patient.

It is an object of the present invention to determine and minimize alocal patient dose applied to a patient in computed tomography.

According to an exemplary embodiment of the present invention, thisobject is solved with a method of determining a local patient doseapplied to a patient in computed tomography comprising the steps ofsegmenting a diagnostic image of an area of interest of the patient anddetermining a dose image showing local patient doses applied to thepatient by using the segmented diagnostic image. Due to the segmentationof the diagnostic image, a local dose delivery to critical anddose-sensitive organs may be determined very accurately and may enablean improved patient dose management.

According to another exemplary embodiment of the present invention asset forth in claim 2, anatomical structures are segmented in thediagnostic image and dose-weighting factors are assigned to theanatomical structures. Advantageously, this allows, for example, fordistinguishing between sensitive and non-sensitive organs of the patientand allows for a very exact determination of the local patient dose.

According to yet another exemplary embodiment according to claim 3 ofthe present invention, a fluence map is determined. Advantageously, thisallows a clinician to immediately determine and to monitor a local dosedelivery to critical and dose-sensitive organs of the patient.

According to another exemplary embodiment of the present inventionaccording to claim 4, the dose image is determined on the basis of thefluence map and the dose-weighting factors. This allows for a veryaccurate determination of the local patient dose applied to the patientwhile being very effective and efficient with respect to computationalefforts. Thus, this exemplary embodiment of the present inventionprovides for a very simple and fast method to determine the localpatient dose.

According to another exemplary embodiment of the present invention asset forth in claim 5, the diagnostic image has grey levels indicatingHounsfield units and the fluence map is determined by filtering the scandata appropriately and back-projecting it using the diagnostic image.This allows for a simple determination of the fluence map. Further, thisexemplary embodiment of the present invention allows for a very accuratedetermination of the fluence map.

According to another exemplary embodiment of the present invention, animage processing device is provided with the features of claim 6, whichallows for a very accurate determination of local patient dose.

Further exemplary embodiments of the image processing device accordingto the present invention, as set forth in claims 6, 7 and 8, provide fora fast and efficient determination of the local patient dose applied tothe patient while minimizing computation efforts and while being veryaccurate.

According to another exemplary embodiment of the present invention asset forth in claim 10, a computer program for an image processing deviceis provided, executing the method according to the present invention.

As described above, CT scanner devices usually produce a diagnosticimage on the basis of the recorded projections acquired during a patientscan, with grey levels indicating Hounsfield units. However, Hounsfieldunits are proportional to linear attenuation coefficients of theunderlining anatomical structure, but differ from the energy absorbedlocally in the patient. Consequently, the absorbed dose distributionwill deviate in a non-linear way from the underlying diagnostic image.According to the present invention, a method and apparatus are providedwhich are able to reconstruct the local dose distribution on the basisof the registered projections (scan data). It may be seen as the gist ofthe invention that the method/apparatus makes twofold use of the scandata as follows: After reconstruction of the scan data into a diagnosticimage, for another time, the scan data are back-projected into thepatient volume using the attenuation information of the diagnostic imageforming a spatially varying photon fluence map as being produced by thex-ray beam incident on the patient. In parallel, the diagnostic image issegmented into anatomical structures (regions with approximatelyconstant attenuation). Dose-weighting factors are assigned which accountfor the difference between locally absorbed energy and photonattenuation. The locally absorbed dose is then calculated on the basisof the fluence map and the corresponding dose weights.

These and other aspects of the present invention will become apparentfrom and elucidated with reference to the embodiments describedhereinafter.

Exemplary embodiments of the present invention will be described in thefollowing, with reference to the following drawings:

FIG. 1 shows a pictorial view of a CT imaging system.

FIG. 2 shows a block schematic diagram of the system illustrated in FIG.1.

FIG. 3 is a flow chart illustrating an exemplary embodiment of asequence of steps executed by the CT imaging system of FIGS. 1 and 2, todetermine a local patient dose applied to a patient.

FIG. 4 is a flow chart illustrating another exemplary embodiment of asequence of steps executed by the CT imaging system of FIGS. 1 and 2, todetermine a local patient dose applied to a patient.

Referring to FIGS. 1 and 2, a computed tomography (CT) imaging system 1is shown. It includes a gantry 2, representative of a “third generation”CT scanner. Gantry 2 has an x-ray source 4 that projects a beam ofx-rays 6 towards a detector array 8 on the opposite side of the gantry2. The detector array 8 is formed by a plurality of detector elements10, which together sense the projected x-rays that pass through anobject, such as depicted in FIG. 1, a medical patient 12. Each detectorelement 10 produces an electrical signal that represents an intensity ofan impinging x-ray beam and hence the attenuation of the beam as itpasses through the object or patient 12. During a scan to acquire x-rayprojection data, the gantry 2 and the components mounted thereon, namelythe x-ray source 4 and the detector 8 with the detector elements 10,rotate about a center of rotation 14. In the embodiment shown in FIG. 2,a plurality of detector elements 10 are arranged in one row, so thatprojection data corresponding to a single image slice is acquired duringa scan. According to another embodiment, the detector elements 10 may bearranged in a plurality of parallel rows, so that projection datacorresponding to a plurality of parallel slices can be acquiredsimultaneously during a scan.

The rotation of the gantry 2 and the operation of x-ray source 4 arecontrolled by a control mechanism 16 of the CT system 1. The controlmechanism 16 includes an x-ray controlling unit 18, which provides thenecessary power and timing signals to the x-ray source 4 and a gantrycontrolling unit 20, which controls the rotational speed and position ofgantry 2 by generating and providing respective control signals to thedrive of the gantry 2.

Reference number 22 designates a data acquisition system provided in thecontrol mechanism (16). The data acquisition system 22 samples analoguedata from the detector elements 10 and converts the data to digitalsignals for subsequent processing.

Furthermore, there is provided an image reconstructuor 24 which receivessamples in digitised x-ray data from the data acquisition system 22 andperforms a high-speed image recognition. Also, there is provided a dosereconstructor 40 for reconstructing a dose which is connected to thedata acquisitions system 22 and to the image reconstructor 24. Insteadof providing a separate image reconstructor 24 and a separate dosereconstructor 40, the function and operation of the image reconstructor24 and the dose reconstructor 40 may be combined in a separate device ormay also be accommodated in the computer 26.

The reconstructed image is applied as an input to the computer 26 whichstores the image in a mass storage device 28, such as a hard disc driveor a floppy drive.

The computer 26 also receives commands and scanning parameters from anoperator via an input device 30, such as a keyboard or pointer device.Furthermore, there may be provided an output device 32 such as a displayor printer, in order to allow the operator to observe the reconstructedimage and other data provided by the computer 26. The operator suppliedcommands and parameters are used by computer 26 to provide controlsignals and information to the data acquisition system 22, to the x-raycontroller 18 and to the gantry controlling unit 20. Furthermore, thecomputer 26 generates output signals output to a table drive controller34 for controlling a movement, position and inclination of the table 36,by providing respective control signals to drive units of the table 26.Thus, the computer 26 controls the position and movement of the patient12 in a gantry opening 38 of the gantry 2. In particular, by themovement of the table 36, the patient 12 is moved through the gantryopening 38.

The data acquisition system 22, the gantry controlling unit 20, thex-ray controlling unit 18, the image reconstructor 24, dosereconstructor 40 and the table drive controller 34 may all be realizedby means of suitable processors or programmable logic controllers, suchas EPLDs distributed by ALTERA in combination with respective poweramplifiers. However, all the operations and functions provided by thedata acquisition system 22, the gantry controlling unit 20, the x-raycontrolling unit 18, the image reconstructor 24, the dose reconstructor40, the output device 32, the data storage 28, the input device 30, thecomputer 26 and the table drive controller 34, may be realized by meansof a computer such as a personal computer with, for example, a Pentiumprocessor.

Image information or data provided by the data acquisition system 22and/or the image reconstructor 24, is referred to as “scan data” in thefollowing:

FIG. 3 shows a flow chart illustrating an exemplary embodiment of asequence of steps of a method according to an exemplary embodiment ofthe present invention, executed by the CT system shown in FIGS. 1 and 2,to determine a local patient dose applied to the patient 12. The stepsS1 to S11 are preferably executed in the data acquisition system 22, thedose reconstructor 40, the image reconstructor 24 and/or the computer26. For storing and outputting, the output device 32 and the datastorage 28 may be used. After the start in step S1, the method continuesto step S2, where the scan data is obtained in known manner. Then, themethod continues to step S3, where the scan data is filtered in knownmanner. Then, in a subsequent step S4, a tomographic reconstruction onthe basis of the filtered scan data is carried out, in order todetermine the diagnostic image of the area of interest of the patient.Usually, the tomographic reconstruction is such that a diagnostic imageis generated with grey levels indicating Hounsfield units. Aftergeneration of the diagnostic image, the method continues to step S5,where the diagnostic image is output to a user or clinician for, e.g.diagnostic purposes.

Then, the method continues to steps S6 to S9 where the data is preparedfor dose reconstruction.

In step S6, the diagnostic image is segmented into anatomical structuresassigned to its voxels. In other words, the diagnostic image issegmented to “material”, where a raw classification (e.g. metal, bone,water, air) based on Hounsfield-thresholds may be sufficient for thispurpose.

In order to transform a fluence F to dose D, dose weighting factors (asindicated as factor prior to the fluence exponential function in thefollowing formulae) are assigned to the anatomical structures in stepS7, based on the already obtained raw segmentation according tomaterial. This may be done by referring to predetermined tables linkingthe respective anatomical structures to predetermined dose-weightingfactors. Anatomical structures are, e.g. bones, muscles, spaces oraccumulations of blood.

Thus, for example a different dose-weighting factor may be assigned tomuscles which are less prone to be damaged by the x-ray beam than, forexamples organs like the liver or parts of the brain. In general, thedose-weighting factors should be determined such that they account bothfor differences between locally absorbed energy and photon attenuationof the respective anatomical structure and for biologically differentsensitivity to dose absorption.

In step S8, the filtered scan data determined in step S3 isback-projected in a way appropriatlely for dose reconstruction and afluence map is reconstructed on the basis of this back-projection. Sincethe scan data is filtered in the same way as in step S3 (for simplicity,but not necessarily with the same filter kernel) as for reconstructingthe Hounsfield image, the filtered data from image reconstruction may besaved in step S3 and re-used here. Advantageously, this allows to reducethe amount of arithmetic calculations.

A straight-forward calculation of total absorbed dose D at a position xin the patient volume carried out in step S8 (S6-S9)—directly expressedby means of the original scan data—can be described with the followingequations: $\begin{matrix}{{{D\left( \underset{\_}{x} \right)} = {S_{0}\mu^{a}*{\int{{\mathbb{d}\theta}\quad{\mathbb{e}}^{- {\int_{0}^{\infty}\quad{{\mathbb{d}\lambda}\quad{\mu{({\underset{\_}{x} + {\lambda{\underset{\_}{e}}_{\theta}}})}}}}}}}}}\quad} & (1) \\{{= {S_{0}\mu^{a}*{\int{\mathbb{d}{\theta\mathbb{e}}^{{- {\int_{0}^{\infty}\quad{{\mathbb{d}\lambda}{\int{{\mathbb{d}{t{\lbrack{{\sigma{({t, \cdot})}}*{k{( \cdot )}}}\rbrack}}}{({{({\underset{\_}{x} + {\lambda{\underset{\_}{e}}_{\theta}}})}\underset{\_}{e}\frac{1}{t}})}}}}}}\quad}}}}}\quad} & (2)\end{matrix}$

μ^(α): material dependent absorption or scatter kernel (3)

θ: gantry angle, i.e x-ray source position (4)

e _(θ):unit vector in direction θ (5)

e _(t) ^(⊥): unit vector orthogonal to direction t (6)

σ( ): scan data (7)

k( ): filter kernel (8) $\begin{matrix}{{d\left( {\underset{\_}{x},\theta} \right)} = {\int{{\mathbb{d}t}{\int_{0}^{\infty}\quad{{\mathbb{d}\lambda}\underset{\equiv {g{({t,\overset{\_}{\lambda},{x\underset{\_}{e}\frac{1}{t}}})}}}{\underset{︸}{\left\lbrack {\sigma\left( {t, \cdot} \right)*{k( \cdot )}} \right\rbrack\left( {{\underset{\_}{xe}\frac{1}{t}} + {\lambda\quad{\sin\left( {\theta - t} \right)}}} \right)}}}}}}} & (9) \\{{= {\int_{0}^{\infty}\quad{{\mathbb{d}\overset{\sim}{\lambda}}{\int{{\mathbb{d}t}\frac{1}{{\sin\left( {\theta - t} \right)}}{g\left( {t,\overset{\sim}{\lambda},{x\underset{\_}{e}\frac{1}{t}}} \right)}}}}}}\quad} & (10) \\{{= {\int{{\mathbb{d}\overset{\sim}{\lambda}}{h\left( {\theta,\overset{\sim}{\lambda},\underset{\_}{x}} \right)}}}}\quad} & (11)\end{matrix}$

g( ): convolution as known from image reconstruction (12)

h( ): point-wise convolution with inverse sinus (13)

In this realisation example, instead of ray-tracing as will be describedwith reference to FIG. 4, the filtered scan data is re-used for dosereconstruction. The fluence F in x is integrated over all views similarto the back-projection method of image reconstruction.

Then, the method continues to step S9, in which a dose image isdetermined in accordance with the above formulae. The dose imagedetermined in step S9 shows local patient doses applied to the patient.The dose image is determined by using the dose-weighting factors and thefluence map.

After the determination of the fluence map, the method continues to stepS10, where the dose-image is output. Then, the method continues to stepS11, where it ends.

According to another exemplary embodiment of the method of determining alocal patient dose applied to a patient according to the presentinvention, the reconstruction of the fluence map and the segmentation ofthe diagnostic image into anatomical structures may be carried out inparallel. This allows for a very fast computation of the dose image.

FIG. 4 shows a flow chart illustrating another exemplary embodiment of asequence of steps of a method according to an exemplary embodiment ofthe present invention, executed by the CT system shown in FIGS. 1 and 2,to determine a local patient dose applied to the patient 12. Step 12 ispreferably executed in the data acquisition system 22, the dosereconstructor 40, the image reconstructor 24 and/or the computer 26. Forstoring and outputting, the output device 32 and the data storage 28 maybe used. Steps S1 to S7 and S10 to S11 are the same as described withreference to FIG. 4.

Firstly, in steps S6 and S7, the reconstructed image is segmentedaccording to “material”, where a raw classification (e.g. metal, bone,water, air) based on Hounsfield-thresholds is sufficient for thispurpose, but more elaborated methods may be used, and dose-weightingfactors are assigned to the anatomical structures. Then, in step S12,for each position of the gantry where a view has been generated, thex-ray source spectrum as known from calibration data is ray-tracedthrough the simulated patient volume as known from step S4, separatedinto voxels with assigned material and corresponding attenuationcoefficients. The absorbed dose is integrated for each voxel. Then, adose image is determined which is output in the subsequent step S10. Inother words, in step S12 the x-ray spectrum is forward-projected and thefluence map is reconstructed on basis of the segmented diagnostic imageand then the dose image is determined that shows local patient dosesapplied to the patient using the dose-weighting factors and the fluencemap.

In brief, according to the present invention, the method/apparatus maketwo-fold use out of the measured scan data. Namely, the scan data isreconstructed into a diagnostic image. Also, the scan data isback-projected into the patient volume, using the attenuationinformation of the diagnostic image forming a spatially varying photonfluence map, as being produced by the x-ray beam incident on thepatient. In parallel, the diagnostic image may be segmented intoanatomical factors, to which dose-weight factors are assigned whichaccount for the difference between locally absorbed energy and photonattenuation. The locally absorbed dose is then calculated on the basisof the fluence map and the corresponding dose weights.

Preferably, the above method/apparatus may be used for CT systems.

1. A method of determining a local patient dose applied to a patient incomputed tomography, the method comprising the steps of: segmenting adiagnostic image of an area of interest of the patient; and determininga dose image showing local patient doses applied to the patient by usingthe segmented diagnostic image.
 2. The method according to claim 1,wherein the step of segmenting the diagnostic image of the area ofinterest of the patient further comprises the steps of: segmenting thediagnostic image into anatomical structures in the area of interest ofthe patient; assigning dose-weighting factors to the anatomicalstructures segmented in the diagnostic image.
 3. The method according toclaim 2, further comprising the step of: determining a fluence map onthe basis of the diagnostic image of an area of interest of the patient.4. The method according to claim 3, wherein the step of determining thedose image showing local patient doses applied to the patient furthercomprises the step of: determining the dose image showing local patientdoses applied to the patient on the basis of the fluence map and thedose-weighting factors.
 5. The method according to claim 3, wherein thediagnostic image has grey levels indicating Hounsfield units and isdetermined from scan data obtained from scanning the area of interest ofthe patient and the fluence map is determined by filtering the scan dataand back-projecting it using information obtained from the previouslydetermined diagnostic image.
 6. An image processing device, comprising:a memory for storing scan data; an image processor for determining alocal patient dose applied to a patient in computed topography, whichprocessor performs the following operation: segmenting a diagnosticimage of an area of interest of the patient; and determining a doseimage showing local patient doses applied to the patient by using thesegmented diagnostic image.
 7. The image processing device according toclaim 6, further performing the operation of: segmenting the diagnosticimage into anatomical structures in the area of interest of the patient;assigning dose-weighting factors to the anatomical structures segmentedin the diagnostic image.
 8. The image processing device according toclaim 7, further performing the operation of: determining a fluence mapon the basis of the diagnostic image of an area of interest of thepatient; and determining the dose image showing local patient dosesapplied to the patient on the basis of the fluence map and thedose-weighting factors.
 9. The image processing device according toclaim 6, wherein the image processing device is part of a computedtomograpy system.
 10. Computer program for an image processing device,for determining a local patient dose applied to a patient in computedtomography, the computer program comprising the steps of: segmenting adiagnostic image of an area of interest of the patient; and determininga dose image showing local patient doses applied to the patient by usingthe segmented diagnostic image.